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5.2- Results
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Once you've got a nice complete set of tables and figures that tell a good story, then it's time to write the results section. I've presented the table that I showed in module one with our hypothetical data, alongside a mock results section that is similar to what I see from a lot of students. One thing I commonly see is that authors spend a lot of time justifying and explaining their statistical approach within the results section.
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In this next module, we’re going to talk about writing the results section. Once you’ve got a nice complete set of tables and figures that tell a good story, then it’s time to write the results section. The results section just falls right out of those tables and figures. The biggest mistake that people make with the results section is that because it falls right out of the tables and figures, there’s a temptation to just repeat to readers, line by line, statistic by statistic, what’s already in the tables. It becomes a reading out of numbers that are already in the tables, but that’s not the point of the results section. The results section is supposed to summarize at a higher level what’s in the tables and figures. You want to point out simple relationships, describe big-picture trends, and just refer the reader to the tables or figures that provide the supporting data. You can highlight a few key numbers for your reader that you think are most important, but don’t simply run through all the numbers that are already available in tables and figures. Here are some examples. So the first reads, over the course of treatment, topiramate was significantly more effective than placebo at improving drinking outcomes on drinks per day, drinks per drinking day, percentage of heavy drinking days, percentage of days abstinent, and log plasma-glutamyl transferase ratio. This study measured a whole bunch of outcomes and you can imagine that if you go to “Table 3”, it’s this big table with all these different outcomes and lots and lots of numbers. But the authors here give a high level summary on all these different outcomes about drinking, the treatment, the drug, beat the placebo. If you want more details, you can go to the table and see more details. The second example says, the total suicide rates for Australian men and women did not change between 1991 and 2000 because marked decreases in older men and women were offset by increases in younger adults, especially younger men. This is refer you to “Table 1”, and you can imagine that what’s in “Table 1” is just a list of the suicide rates from 1991 to 2000, broken down by gender and age. It may be hard for readers to scroll through the table and make sense of all those numbers, but the author is summarizing the trends in the data set. There are no changes overall during this period, but if you look at certain subsets, there’s a decrease in one group and an increase in another. They point out these trends without giving any specific numbers. The reader can go to the table to see the specific numbers. This is what the results section should look like. Notice it’s very succinct. Each table is summarized in just a sentence. Now here is an example of what not to do. I’m gonna go back to the hypothetical example that I had on bad witches and good witches. That bad witches remember were older, less healthy, they exercise less and so on. I’ve presented the table that I showed in module one with our hypothetical data, alongside a mock results section that is similar to what I see from a lot of students. The results section starts, the characteristics of the bad witches and the good witches are shown in “Table 1”, and I want to just point out here that they are shown– that’s in the passive voice. And then the writer launches into a reading out of the table. The mean age of the bad witches was 45 ± 5, and the mean age of the good witches was 36 ± 6. Then the author tells us that gender was similar between the groups with 85% female in the bad witches and 83% female in the good witches and then the writer moves on to present the exact numbers for BMI, blood pressure, and so on. You can see that the author is literally just reading the table for the reader, line by line, number by number. You have to give your reader more credit than this. The reader can go to the table and get all those details themselves. Your job in the results section is to give a higher level summary. What’s the take home message of the table? What do you want your readers to pay attention to? So if a student gave me something like this, here’s how I would edit that. My edited version starts, the witches were on average, lean and predominantly female (Table 1). Notice that I didn’t waste a sentence exclusively telling the reader that “Table 1” shows the descriptive characteristics of the groups. I just launched right into the take home messages from “Table 1”, insided the table in parentheses. You have to trust your reader. It’s obvious to the reader that it’s a table of descriptive characteristics. So don’t waste a sentence stating the obvious. It just closed your reader down. Then I just go through the high level comparison of the two groups. Bad witches were significantly older, had higher blood pressure, exercised less, and we’re more likely to smoke than good witches. More bad witches were unemployed, but this difference did not reach statistical significance. Notice that I didn’t present any numbers. The key here is to point out how the two groups differ at a high level. The reader can refer to the table for specific numbers. In some result sections, I might include one or two key numbers that I really want to highlight for the reader. Okay, so notice the edited version here. It’s much easier to read, it’s less tedious, and it’s more useful to the reader because it gives only the key points. Here are some tips for writing your results section. If the results are long or complex, consider breaking the results into subsections with informative headings. This is not always needed but it can provide a helpful road map for the reader particularly if there are lot of results to read through. As I’ve already talked about, the information in the results section should complement rather than repeat what’s in the tables and figures. For example, if you are presenting a figure like a bar graph that doesn’t have precise numbers, you could give some of the precise numbers in the text, or if you presented the means of two groups in the table, you could in the text report the percent difference in those two groups, so a slightly different take on those numbers. For example, rather than repeating that good witches exercised 60 minutes a day and bad witches 30 minutes a day, you could say that good witches exercised twice as long as bad witches that would complement the information in the table. You can repeat or highlight the most important numbers from the table. For example, if your study is a randomized placebo control, trial of a new drug to reduce blood pressure, then the main point of the study is to estimate the difference in blood pressure reduction between the drug and placebo groups. So that number probably belongs in the text, you want to highlight it. Don’t forget that negative results are just as important as positive results, and if you have a control group, the most important comparison is the active treatment versus the control. So make sure you are highlighting that comparison in the results. Another tip, reserve the term significant to mean statistically significant just to avoid any confusion. Also try not to mix results with methods. One thing I commonly see is that authors spend a lot of time justifying and explaining their statistical approach within the results section. They feel like they need to give the rationale for which models they ended up using. They feel like they need to give that within the results section, but this is confusing for the reader. The results section is about what you found, not what you did. So justify and explain the statistical approach within the method section, then in the results section, just tell the reader what those statistical models revealed. Similarly, you don’t want to mix up the results section with the discussion section. The results section is about what your data show. The discussion section is about what your data mean. So concentrate on the basic findings in the results section and leave the interpretation of those findings for the discussion. Authors also get very confused about what verb tense to use, but it’s actually pretty straightforward. The rule is that if you’re talking about completed actions, things that are already finished such as the experiments and analysis, use the past tense. So you would say, we found that, because you found it in the past, or the average reaction time was, because the experiment that measured reaction times has already been completed in the past, or women were more likely to, or men smoked more cigarettes than, because again these experiments were completed in the past. But if you’re talking about assertions that continue to be true such as what the tables show or what the data suggest, these statements belong in the present tense because it’s still true when your reader reads the paper that “Figure 1” shows the means of the groups. This continues to be true. So if you say “Figure 1” shows, you should put that in the present tense because the figure is still showing that when the reader reads the paper, or you would say the findings confirm, that’s still true, the data suggest, or we believe that this shows because those things are still true at the time the reader reads the paper. Those belong in the present tense. Just to give you a few examples on verb tense, here’s a result section. They say information was available for 7766 smokers. Of these, 1216 were classified, notice the passive voice here, as hardcore smokers. But then we get “Table 1” gives, so we start with the past tense, all the experiments that were completed, but then when we talk about the table, we put it in the present tense. “Table 1” gives, because “Table 1” is still giving those characteristics presently, and then everything else in this paragraph is in the past tense because it’s talking about things that were already measured in the completed study. Finally, I strongly recommend using the active voice in the results section. As we’ve talked about, it’s more lively and easier to read than the passive voice, and people worry about using the active voice in results because they feel like they’ll end up starting every sentence with we, we found, we observed, but that’s not the case in the results section. You can talk about the study participants, the experimental outputs, the data models, and so on, so there’s lots of other options for the subject of the sentence besides we. So it’s fairly easy to put the results section in the active voice. Just to give you an example, notice that this study broke the results section into subsections with headings, which I’ve mentioned before can be helpful. This subsection is comparing attitudes and beliefs in smokers with low versus high dependence, as well as in hardcore smokers versus non-hardcore smokers. But notice the paragraph is in the active voice as well as the past tense. So we compared beliefs were smokers agreed, differentiation emerged. It’s nice and lively and easy to read and the authors only used we once as the subject of the sentence. They were able to find other subjects. They talked about the smokers or the differentiation. So for the results section, use the active voice.
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